ReviewElectrophoresis2021
New insights into the conversion of electropherograms to the effective electrophoretic mobility scale.
Review in Electrophoresis, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Capillary Electrophoresis-Mass Spectrometry at Trial by Metabo-Ring: Effective Electrophoretic Mobility for Reproducible and Robust Compound Annotation.Analytical chemistry · 2020Trial
- A Software Tool for Rapid and Automated Preprocessing of Large-Scale Serum Metabolomic Data by Multisegment Injection-Capillary Electrophoresis-Mass Spectrometry.Analytical chemistry · 2025Article
- CE-MS-Based Clinical Metabolomics of Human Plasma.Methods in molecular biology (Clifton, N.J.) · 2025Article
- [Progress of highly reproducible capillary electrophoresis].Se pu = Chinese journal of chromatography · 2024Article
- Capillary electrophoresis-mass spectrometry as a tool for Caenorhabditis elegans metabolomics research.Metabolomics : Official journal of the Metabolomic Society · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
CE-MS is increasingly gaining momentum as an analytical tool in metabolomics, due to its ability to obtain information about the most polar elements in biological samples. This has been helped by improvements of robustness in peak identification by means of mobility-scale representations of the electropherograms (mobilograms). As a necessary step toward facilitating the use of CE-MS for untargeted metabolomics data, the authors previously developed and introduced ROMANCE, a software automating mobilogram generation for large untargeted datasets through a simple and self-contained user interface. Herein, we introduce a new version of ROMANCE including new features such as compatibility with other types of data (targeted MS data and 2D UV-Vis absorption-like electropherograms), and the much needed additional flexibility in the transformation parameters (including field ramping and the use of secondary markers), more measurement conditions (depending on detection and integration modes), and most importantly tackling the issue of quantitative peak conversion. First, we present a review of the current theoretical framework with regard to peak characterization, and we develop new formulas for multiple marker peak area corrections, for anticipating peak position precision, and for assessing peak shape distortion. Then, the new version of the software is presented and validated experimentally. We contrast the multiple marker mobility transformations with previous results, finding increased peak position precision, and finally we showcase an application to actual untargeted metabolomics data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.